SIVOCS

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# SIVOCS

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# B1 (NEW): Kruskal-Wallis test: SI familiarity depends on sci. domains?

```
## 
## 	Bartlett test of homogeneity of variances
## 
## data:  familiarWithSI.response. by domain
## Bartlett's K-squared = 12.931, df = 2, p-value = 0.001556
```

```
## 
## 	Kruskal-Wallis rank sum test
## 
## data:  familiarWithSI.response. by domain
## Kruskal-Wallis chi-squared = 45.694, df = 2, p-value = 1.196e-10
```

* Mean ranks of the groups are not the same, SI fam. depends on domain

---

## 
##     Bartlett test of homogeneity of variances
## 
## data:  familiarWithSI.response. by domain
## Bartlett's K-squared = 12.931, df = 2, p-value = 0.001556

---

# B1: Wilcox test: SI familiarity depends on sci. domains?

.pull-left[
* SSH vs other

```
## 
## 	Wilcoxon rank sum test with continuity correction
## 
## data:  familiarWithSI.response. by SSH
## W = 8590, p-value = 2.001e-11
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  -3.000023 -1.999999
## sample estimates:
## difference in location 
##              -2.000026
```

]

.pull-right[
* NS vs other

```
## 
## 	Wilcoxon rank sum test with continuity correction
## 
## data:  familiarWithSI.response. by Math._Natur._and_Eng.
## W = 17358, p-value = 0.003771
## alternative hypothesis: true location shift is not equal to 0
## 95 percent confidence interval:
##  0.0000604398 1.0000123644
## sample estimates:
## difference in location 
##              0.9999553
```
]

---

# B1: *Familiarity with SI* across scientific domains

<br>

* *Familiarity with SI* differs across scientific domains (ANOVA test: p &lt; 0.05)
* *Biology and Medicine* and *Math., Natur, and Eng. Sci.* are similar (pairwise t-test: p &gt; 0.05)
* *Humanities and Social Sciences* are significantly different than the others (pairwise t-test with each: p &lt; 0.05)